A Real-Time Energy Management Strategy for Parallel HEVs with MPC

Abstract

In this paper, a real-time energy management for parallel hybrid electric vehicles (HEVs) to improve fuel efficiency is presented. A two-level optimal controller using model predictive control (MPC) scheme is designed to realize the energy management. The first level is designed to decide the operating mode with a simple rule-based block. In order to realize the total minimization of fuel and power, a nonlinear optimal control problem based MPC is formulated to generate the optimal power split and gear ratio schedule in the second level. The multiple shooting algorithm is introduced to decouple the dynamic constraints. After that the proposed optimal problem is converted into a nonlinear optimization problem with the extra variables. Then the problem is solved using sequential quadratic programming (SQP) method. A virtual traffic simulation platform CarMaker is built to emulate the real driving conditions. A co-simulation platform can be designed with MATLAB/Simulink and CarMaker which is called traffic-in-the-loop-platform (TILP). The proposed controller can implement in the TILP platform without relying on predefined route.